Application of Data Mining for Slot Time Prediction at International Airports in Indonesia: J48 Algorithm


  • Renddy Wandhana Suryaman Bina Nusantara University
  • Gunawan Wang Bina Nusantara University
  • Viany Utami Tjhin Bina Nusantara University



Data mining, J48, Decision Tree, Naïve Bayes, Slot time



In aviation, the safety and smooth flow of flight traffic is a business core, where every flight traffic service is expected to avoid delays caused by aircraft movement either in the air or on land. Therefore, the time slot at the airport is essential for the accuracy of the movement of aircraft, both Departure and Arrival, and this is intended to avoid delays caused by the accumulation of queues of planes that will depart and planes that will land, with a large number of aircraft movements at the International Airport. Soekarno Hatta requires analysis with data mining techniques such as the J48 algorithm and Decision Tree, and Naïve Bayes.




I. Artamonov, N. Danilochkina, I. Pocebneva, and K. Karmokova, “Using data integrity models for aviation industry business process quality management,” Transp. Res. Procedia, vol. 63, pp. 1668–1673, 2022.

S. Bhargav and N. Mehra, “Study of employee attrition in business process outsourcing companies in India,” Int. J. Res. Soc. Sci., vol. 8, no. 9, pp. 348–358, 2018.

A. Bitkowsk, “The relationship between Business Process Management and Knowledge Management-selected aspects from a study of companies in Poland,” J. Entrep. Manag. Innov., vol. 16, no. 1, pp. 169–193, 2020.

P. Balakrishna, R. Ganesan, and L. Sherry, “Accuracy of reinforcement learning algorithms for predicting aircraft taxi-out times: A case-study of Tampa Bay departures,” Transp. Res. Part C Emerg. Technol., vol. 18, no. 6, pp. 950–962, 2010.

G. Praetorius, F. van Westrenen, D. L. Mitchell, and E. Hollnagel, “Learning lessons in resilient traffic management: a cross-domain study of vessel traffic service and air traffic control,” in HFES Europe Chapter Conference Toulouse 2012, 2012, pp. 277–287.

S. Hamzah and S. A. Adisasmita, “Aircraft parking stands: proposed model for Indonesian airports,” Procedia Environ. Sci., vol. 28, pp. 324–329, 2015.

R. Kurniawan, A. Sutawan, and R. Amalia, “Information System Ordering Online Restaurant Menu At Hover Cafe,” Aptisi Trans. Manag., vol. 4, no. 1, pp. 32–40, 2020.

E. Chowns, “Is community management an efficient and effective model of public service delivery? Lessons from the rural water supply sector in Malawi,” Public Adm. Dev., vol. 35, no. 4, pp. 263–276, 2015.

A. Carlin and R. E. Park, “Marginal cost pricing of airport runway capacity,” Am. Econ. Rev., vol. 60, no. 3, pp. 310–319, 1970.

M. Doepke and M. Tertilt, “Does female empowerment promote economic development?,” J. Econ. Growth, vol. 24, no. 4, pp. 309–343, 2019.

A. Alwiyah, S. Sayyida, P. A. Sunarya, and D. Apriliasari, “Inovasi Manajemen Pengajuan Judul Kuliah Kerja Praktek (KKP) berbasis Laravel Framework,” Technomedia J., vol. 7, no. 2, pp. 168–180, 2022.

I. Amsyar, E. Cristhopher, U. Rahardja, N. Lutfiani, and A. Rizky, “Application of Building Workers Services in Facing Industrial Revolution 4.0,” Aptisi Trans. Technopreneursh., vol. 3, no. 1, pp. 32–41, 2021




How to Cite

Renddy Wandhana Suryaman, Gunawan Wang, & Viany Utami Tjhin. (2022). Application of Data Mining for Slot Time Prediction at International Airports in Indonesia: J48 Algorithm . Aptisi Transactions on Technopreneurship (ATT), 4(3), 215–225.